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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_One Factor ANOVA.wasp
Title produced by softwareOne-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)
Date of computationThu, 20 Dec 2012 18:00:59 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Dec/20/t1356044624wmhdfbp19o3tuyv.htm/, Retrieved Fri, 01 Nov 2024 00:37:40 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=203201, Retrieved Fri, 01 Nov 2024 00:37:40 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact152
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Two-Way ANOVA] [] [2010-11-02 14:42:14] [b98453cac15ba1066b407e146608df68]
- R P   [Two-Way ANOVA] [] [2012-10-15 23:19:27] [0208c1f08efc8e25366206e954253d87]
- RMPD      [One-Way-Between-Groups ANOVA- Free Statistics Software (Calculator)] [] [2012-12-20 23:00:59] [1fa8d8a5ead94b4e7273b6802fa6471c] [Current]
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Dataseries X:
0	'NoTreatment'
0	'Treatment'
0	'NoTreatment'
0	'NoTreatment'
1	'NoTreatment'
0	'Treatment'
1	'NoTreatment'
0	'NoTreatment'
0	'Treatment'
0	'NoTreatment'
0	'Treatment'
0	'NoTreatment'
0	'NoTreatment'
0	'NoTreatment'
0	'NoTreatment'
0	'NoTreatment'
0	'NoTreatment'
0	'NoTreatment'
0	'Treatment'
0	'NoTreatment'
0	'NoTreatment'
0	'Treatment'
0	'NoTreatment'
0	'NoTreatment'
1	'Treatment'
0	'Treatment'
0	'NoTreatment'
0	'Treatment'
0	'NoTreatment'
0	'NoTreatment'
0	'NoTreatment'
0	'NoTreatment'
0	'NoTreatment'
0	'NoTreatment'
0	'NoTreatment'
0	'NoTreatment'
0	'Treatment'
1	'NoTreatment'
0	'NoTreatment'
0	'Treatment'
1	'NoTreatment'
0	'NoTreatment'
0	'NoTreatment'
0	'NoTreatment'
0	'NoTreatment'
0	'NoTreatment'
0	'NoTreatment'
0	'NoTreatment'
0	'NoTreatment'
0	'NoTreatment'
1	'NoTreatment'
1	'Treatment'
0	'Treatment'
0	'NoTreatment'
0	'NoTreatment'
0	'Treatment'
0	'NoTreatment'
1	'NoTreatment'
1	'NoTreatment'
0	'Treatment'
0	'Treatment'
0	'Treatment'
0	'NoTreatment'
1	'NoTreatment'
0	'NoTreatment'
0	'NoTreatment'
1	'NoTreatment'
0	'NoTreatment'




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=203201&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=203201&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=203201&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







ANOVA Model
Useful ~ T20
means0.176-0.059

\begin{tabular}{lllllllll}
\hline
ANOVA Model \tabularnewline
Useful  ~  T20 \tabularnewline
means & 0.176 & -0.059 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=203201&T=1

[TABLE]
[ROW][C]ANOVA Model[/C][/ROW]
[ROW][C]Useful  ~  T20[/C][/ROW]
[ROW][C]means[/C][C]0.176[/C][C]-0.059[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=203201&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=203201&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

ANOVA Model
Useful ~ T20
means0.176-0.059







ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
T2010.0440.0440.3170.575
Residuals669.1760.139

\begin{tabular}{lllllllll}
\hline
ANOVA Statistics \tabularnewline
  & Df & Sum Sq & Mean Sq & F value & Pr(>F) \tabularnewline
T20 & 1 & 0.044 & 0.044 & 0.317 & 0.575 \tabularnewline
Residuals & 66 & 9.176 & 0.139 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=203201&T=2

[TABLE]
[ROW][C]ANOVA Statistics[/C][/ROW]
[ROW][C] [/C][C]Df[/C][C]Sum Sq[/C][C]Mean Sq[/C][C]F value[/C][C]Pr(>F)[/C][/ROW]
[ROW][C]T20[/C][C]1[/C][C]0.044[/C][C]0.044[/C][C]0.317[/C][C]0.575[/C][/ROW]
[ROW][C]Residuals[/C][C]66[/C][C]9.176[/C][C]0.139[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=203201&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=203201&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

ANOVA Statistics
DfSum SqMean SqF valuePr(>F)
T2010.0440.0440.3170.575
Residuals669.1760.139







Tukey Honest Significant Difference Comparisons
difflwruprp adj
Treatment-NoTreatment-0.059-0.2670.150.575

\begin{tabular}{lllllllll}
\hline
Tukey Honest Significant Difference Comparisons \tabularnewline
  & diff & lwr & upr & p adj \tabularnewline
Treatment-NoTreatment & -0.059 & -0.267 & 0.15 & 0.575 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=203201&T=3

[TABLE]
[ROW][C]Tukey Honest Significant Difference Comparisons[/C][/ROW]
[ROW][C] [/C][C]diff[/C][C]lwr[/C][C]upr[/C][C]p adj[/C][/ROW]
[ROW][C]Treatment-NoTreatment[/C][C]-0.059[/C][C]-0.267[/C][C]0.15[/C][C]0.575[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=203201&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=203201&T=3

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Tukey Honest Significant Difference Comparisons
difflwruprp adj
Treatment-NoTreatment-0.059-0.2670.150.575







Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group10.3170.575
66

\begin{tabular}{lllllllll}
\hline
Levenes Test for Homogeneity of Variance \tabularnewline
  & Df & F value & Pr(>F) \tabularnewline
Group & 1 & 0.317 & 0.575 \tabularnewline
  & 66 &   &   \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=203201&T=4

[TABLE]
[ROW][C]Levenes Test for Homogeneity of Variance[/C][/ROW]
[ROW][C] [/C][C]Df[/C][C]F value[/C][C]Pr(>F)[/C][/ROW]
[ROW][C]Group[/C][C]1[/C][C]0.317[/C][C]0.575[/C][/ROW]
[ROW][C] [/C][C]66[/C][C] [/C][C] [/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=203201&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=203201&T=4

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Levenes Test for Homogeneity of Variance
DfF valuePr(>F)
Group10.3170.575
66



Parameters (Session):
par1 = 1000 ; par2 = 0.05 ; par3 = 0.95 ; par4 = 0.36 ; par5 = 0.50 ;
Parameters (R input):
par1 = 1 ; par2 = 2 ; par3 = TRUE ;
R code (references can be found in the software module):
par3 <- 'FALSE'
par2 <- '2'
par1 <- '1'
cat1 <- as.numeric(par1) #
cat2<- as.numeric(par2) #
intercept<-as.logical(par3)
x <- t(x)
x1<-as.numeric(x[,cat1])
f1<-as.character(x[,cat2])
xdf<-data.frame(x1,f1)
(V1<-dimnames(y)[[1]][cat1])
(V2<-dimnames(y)[[1]][cat2])
names(xdf)<-c('Response', 'Treatment')
if(intercept == FALSE) (lmxdf<-lm(Response ~ Treatment - 1, data = xdf) ) else (lmxdf<-lm(Response ~ Treatment, data = xdf) )
(aov.xdf<-aov(lmxdf) )
(anova.xdf<-anova(lmxdf) )
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'ANOVA Model', length(lmxdf$coefficients)+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, paste(V1, ' ~ ', V2), length(lmxdf$coefficients)+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'means',,TRUE)
for(i in 1:length(lmxdf$coefficients)){
a<-table.element(a, round(lmxdf$coefficients[i], digits=3),,FALSE)
}
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'ANOVA Statistics', 5+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, ' ',,TRUE)
a<-table.element(a, 'Df',,FALSE)
a<-table.element(a, 'Sum Sq',,FALSE)
a<-table.element(a, 'Mean Sq',,FALSE)
a<-table.element(a, 'F value',,FALSE)
a<-table.element(a, 'Pr(>F)',,FALSE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, V2,,TRUE)
a<-table.element(a, anova.xdf$Df[1],,FALSE)
a<-table.element(a, round(anova.xdf$'Sum Sq'[1], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'Mean Sq'[1], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'F value'[1], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'Pr(>F)'[1], digits=3),,FALSE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residuals',,TRUE)
a<-table.element(a, anova.xdf$Df[2],,FALSE)
a<-table.element(a, round(anova.xdf$'Sum Sq'[2], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'Mean Sq'[2], digits=3),,FALSE)
a<-table.element(a, ' ',,FALSE)
a<-table.element(a, ' ',,FALSE)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
bitmap(file='anovaplot.png')
boxplot(Response ~ Treatment, data=xdf, xlab=V2, ylab=V1)
dev.off()
if(intercept==TRUE){
'Tukey Plot'
thsd<-TukeyHSD(aov.xdf)
bitmap(file='TukeyHSDPlot.png')
plot(thsd)
dev.off()
}
if(intercept==TRUE){
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Tukey Honest Significant Difference Comparisons', 5,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, ' ', 1, TRUE)
for(i in 1:4){
a<-table.element(a,colnames(thsd[[1]])[i], 1, TRUE)
}
a<-table.row.end(a)
for(i in 1:length(rownames(thsd[[1]]))){
a<-table.row.start(a)
a<-table.element(a,rownames(thsd[[1]])[i], 1, TRUE)
for(j in 1:4){
a<-table.element(a,round(thsd[[1]][i,j], digits=3), 1, FALSE)
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
}
if(intercept==FALSE){
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'TukeyHSD Message', 1,TRUE)
a<-table.row.end(a)
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Must Include Intercept to use Tukey Test ', 1, FALSE)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable2.tab')
}
library(car)
lt.lmxdf<-leveneTest(lmxdf)
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Levenes Test for Homogeneity of Variance', 4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,' ', 1, TRUE)
for (i in 1:3){
a<-table.element(a,names(lt.lmxdf)[i], 1, FALSE)
}
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Group', 1, TRUE)
for (i in 1:3){
a<-table.element(a,round(lt.lmxdf[[i]][1], digits=3), 1, FALSE)
}
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,' ', 1, TRUE)
a<-table.element(a,lt.lmxdf[[1]][2], 1, FALSE)
a<-table.element(a,' ', 1, FALSE)
a<-table.element(a,' ', 1, FALSE)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')